Description

Computes the prediction errors using the trained models.

Usage

1

Arguments

models

A list of trained models for the genes of interest.

At the moment the collection of trained models returned
by FIT::train() cannot be directly passed to FIT::predict():
the user has to explicitly convert it to an appropriate format by using
FIT::train.to.predict.adaptor().
(This restriction might be removed in a future.)

expression

An object that represents the actual measured data of
gene expressions.
The object can be created from a dumped/saved dataframe
of size nsamples * ngenes
using FIT::load.expression().
(At the moment it is an instance of a hidden class IO$Attribute,
but this may be subject to change.)

attribute

An object that represents the attributes of
microarray/RNA-seq data.
The object can be created from a dumped/saved dataframe
using FIT::load.attribute().
(At the moment it is an instance of a hidden class IO$Attribute,
but this may be subject to change.)

weather

An object that represents actual or hypothetical weather data
with which predictions of gene expressions are made.
The object can be created from a dumped/saved dataframe
using FIT::load.weather().
(At the moment it is an instance of a hidden class IO$Weather,
but this may be subject to change.)

Value

A list of deviance (a measure of validity of predictions,
as is defined by each model) between the prediction results
and the measured results (as is provided by the user through
expression argument).